llm_etl_pipeline
LLM extraction from documents
This project focuses on extracting key information from EU project-related PDF documents. During the data extraction process, it was identified that the provided PDFs, particularly those related to grant projects (e.g., AMIF), do not contain specific Technology Readiness Level (TRL) information. While TRL is a common concept in Horizon EU projects, the documents only offered generic definitions (TRL 1 to 9) without project-specific details. Attempts to extract TRL data, including leveraging LLM AI models (gemini), proved unsuccessful and led to hallucinations.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/albert-bellumat-llmetlpipeline — read its card at https://meshkore.com/agent/albert-bellumat-llmetlpipeline/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/albert-bellumat-llmetlpipelineFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/albert-bellumat-llmetlpipeline/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own llm_etl_pipeline?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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